Consultant - Advanced Analytics, GIC SC Analytics

COMPANY OVERVIEW We exist to make food the world loves. But we do more than that. Our company is a place that prioritizes being a force for good, a place to expand learning, explore new perspectives and reimagine new possibilities, every day. We look for people who want to bring their best — bold thinkers with big hearts who challenge one another and grow together. Because becoming the undisputed leader in food means surrounding ourselves with people who are hungry for what’s next.​

OVERVIEW

Supply chain analytics group is responsible for delivering the solutions and developing the capabilities which enables better decision-making in supply chain This role is in the Segment analytics team that supports the Segment teams by developing advanced analytics solutions to identify and analyze opportunities corresponding to variety of SC Analytics problem statements. The primary responsibilities of this job are to develop innovative solutions by leveraging analytics techniques like descriptive, diagnostic, predictive and prescriptive modeling, statistical analysis and operations research techniques. This is an individual contributor role that includes project lead responsibilities, stakeholder management, project management, coaching and mentoring the analysts in the team. This role requires to operate in 1.30pm to 10.30 pm shift.   KEY ACCOUNTABILITIES

Requirement Gathering and Project Management (20% of Time) Partner with supply chain stakeholders to understand business decisions, operational context, constraints, and desired outcomes, translating ambiguous questions into clear analytical problems, hypotheses, scope, and success measures. Select the right approach—statistical analysis, machine learning, forecasting, experimentation, or operations research—while assessing data readiness, risks, dependencies, feasibility, priorities, and milestones. Analytics Models design, development & Improve (40% of Time) Ideate and execute improvements that drive efficiency, standardization, and scalable solutions through historical data analysis and machine learning. Develop analytical models across descriptive, diagnostic, predictive, and prescriptive analytics, including feature engineering and automated testing. Explain and deploy model recommendations to cross-functional stakeholders while supporting enhancements and bug fixes for existing models. Output (20% of Time) Provide actionable insights through effective presentations and visualizations while deploying, documenting, and sustaining models and applications using DevOps/MLOps practices. Training / Knowledge (20% of Time) Mentor and train team members in data preparation, diagnostics, predictive analytics, R, Python, and supply chain analytics. Standardization and document processes, working on individual development plans, and contribute to data science processes, frameworks, tools, and standards.   MINIMUM QUALIFICATIONS

Education:  Full-Time graduation from an accredited university (Mandatory). Experience:  At least 4 years of relevant experience in analytics, data science, machine learning, or a closely related field. Technical Skills:  Experience in descriptive, diagnostic, predictive, and prescriptive analytics; proficiency in R, Python, intermediate SQL, Excel, and Power BI; and a strong understanding of end-to-end supply chain operations. Soft Skills: Lead and develop analytical capabilities with strong problem-solving, learning agility, and independent decision-making. Engage stakeholders and lead projects collaboratively, applying strong project management and organizational skills. Explain analytical findings, assumptions, model behavior, and limitations clearly while energizing teams and supporting cross-functional collaboration.

PREFERRED QUALIFICATIONS

Master’s degree with 5+ years of relevant experience in Operations Research, Analytics, Mechanical, Industrial or Production Engineering, or Statistics. Experience working on DevOps/MLOps, Git & GCP.

ELIGIBILITY Applicants must meet minimum age qualifications in the country in which the job is located.